The Urban Design of Distributed Energy Resources
By
ARCHIVES
MASSACHUSETTS INSTIUTE
OF TECH-LOYY
Travis Sheehan
FEB 2 4 2T12
Bachelor of Design
University of Florida
Gainesville, Florida (2008)
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Submitted to the Department of Architecture and Department of Urban Studies and
Planning
in partial fulfillment of the requirements for the degrees of
Master in City Planning
and
Master of Architecture
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
February 2012
( 2012 Travis Sheehan. All Rights Reserved
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p1
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1/12/2012
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Norn an B. and Muriel Leventhal Professor of Urban Design
Thesis Supervisor
Certified by
Kent Larson
Principal Research Associate
Thesis Supervisor
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Accepted by
1/
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es d Planning
Department of Urban
'Professor
Accepted by
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Chair, Department Committee on Graduate Students
Department of Architecture
The Urban Design of Distributed Energy Resources
Maximizing Load Diversity through Building-Mix Optimization
By
Travis Sheehan
Submitted to the Department of Urban Studies and Planning and Department of Architecture
On January 18, 2010 in partial fulfillment of the requirements for the degree of
Master in City Planning
and
Master of Architecture
Abstract
Distributed energy resources (DERs) are a considerable research focus for cities to
reach emissions reduction goals and meet growing energy demand. DERs, consisting of local power plants and distribution infrastructure, range from urban to neighborhood scale. In optimizing neighborhood scale DERs, one of the many design decisions is a desirable mix of building types to balance energy demand through daily and
annual cycles. However, real estate development drives use-mix primarily through
market demand forcasts and financial value creation. The research presented here
answers two questions: (1)What are the impacts of altering use-mix to conform to a
desired energy profile? and (2) Can site design overcome regulatory and perceptual
barriers when integrating DERs at the neighborhood scale? These questions are explored through a review of existing incentives and barriers to district energy systems
- including policy, real estate, technical, and design issues. Next I identify within
a test site, at the neighborhood scale, the energy and design characteristics pertinent to the research presented here. Ultimately, I propose an analysis framework to
examine the energy-form-finance issues encountered when planning a neighborhood
scale energy district. Using the resulting framework, I perform a sensitivity analysis that measures the financial impact of altering use-mix to balance energy loads.
Finally, I propose an appropriate site design informed by the review and analysis.
Recent policies like the Murton Rule in London, which offer incentives for small power
plants, have increased the popularity of the neighborhood scale district energy systems. Though the literature covers financial, regulatory, and engineering aspects of
these systems, few studies explore the impact of DERs on urban form at the neighborhood scale. This thesis demonstrates that issues of meeting real estate demands and
power demands can be resolved elegantly if one approaches the problem holistically.
Thesis Supervisors:
Dennis Frenchman, Leventhal Professor of Urban Design and Planning
Kent Larson, Principal Research Associate
Thesis Reader:
Stephen Hammer, Lecturer in Energy Planning
41
ACKNOWLEDGMENTS
My dearest family, a south Floridian dream. Their constant reassurance in my talents, their
devoted affection, and their unwavering availability has brought me here today. I send my
deepest gratitude to my Mom, Dad, Brother, Sister, Ivan and Oliver.
My advisers, a diverse and powerful team. Their unwavering support, prompt availability,
project pacing, and guidance through problem formulation has equipped me with irreplaceable
research experience. I send my earnest gratitude to Dennis, Kent, and Stephen (the Hammer).
Your patience and kindness was priceless.
My MITsupport people and alumni network, an open source system. Their persistent availability,
shared resources, and genuine concern has granted me an arsenal of knowledge and technical
ability. I send my warmest thanks to Duncan (Dun-Can), Cynthia Stewart, Annette HorneWilliams, Tom Fitzgerald, Sandy Welford, Sandra Elliot, Alstan, Cristoph Reinhart, Eran BenJoseph, Karl Seidman, Shalom Flank, and Patrick Haswell.
My friends, a multidisciplinary mash-up. Their loving kindness, knowledge, laughter,
sympathy, expertise, ignorance, open mindedness and diehard work-ethic has affirmed a
collective goodwill in the future of planning, design and innovation. I send my best memories
and intentions to Daniel Dao (lAM), Lee Dykxhoorn, Jaclyn DeVore, Tarek Rahka, Ira Winder,
Reilly and Mehmet, Stephen Form, Joel Batson, Justin Zorn, Meredy Throop, Buck Sleeper,
Sara Zewde, Ajay Prasad, Trish Ramaccia, Cristophe Chung, Jaymes Dunsmore, Rico Suarez,
Haley Heard, Liz DiLorenzo, Corey Wowk and many, many more.
And finally to my thesis helpers, the unexpected angels. Their blind giving reaffirms the basic
goodwill in all of us to give without any intention of receipt. I send vibrant thanks to Susanna,
Claudia, Evelyn and Jasmine.
CONTENTS
PART I - CONTEXT
Chapter I - Introduction
11
Chapter l- Site and Data Sources
19
PART 11- DISTRIBUTED ENERGY RESOURCES OVERVIEW
Chapter III - Demands of Real Estate and Power System
31
Chapter IV- National and Local Policies and Barriers
41
PART III - ENERGY PLANNING ANALYSIS
Chapter V - Analysis of Existing Schemes
57
Chapter VI - Use-Mix Sensitivity Analysis
69
PART IV- SITE PROPOSAL
Chapter VII - Urban and Architecture Design Proposal
83
Conclusions and Next Steps
101
List of Figures and Illustration Credits
109
Bibliography
113
81
PART I
101
Chapter I
Introduction
1.1 Problem Statement
Urban environments are the top consumers of energy in the world, accounting for up to 80% of global carbon emissions (World Bank 2010). From redevelopment sites in thriving cities to rapidly urbanizing greenfields in developing regions,
dense urban patterns enable a potentially sustainable future. Within the many complex systems of cities, energy production and distribution is of great concern. Energy production and demand through building stock accounts for approximately 40% of carbon emissions in the United States. Cities of many scales incorporate
plans for energy systems in reaction to escalating fuel costs and energy insecurity.
Municipalities are planning distributed energy resources (DER) to meet growing
energy demands and to increase the efficiency of the primary fuel use to produce cooling, heating, and electricity (See Figure 1) Small scale power plants that implement
cooling heating power technology (CHP) use the waste heat from electric production,
making them 25% more efficient than conventional electric production and saving sig-
nificant carbon emissions.' This thesis asks: How can city planners and urban
designers reshape urban energy systems with distributed energy resources?
Although state and federal regulations impact the feasibility of DER, urban planners may have an impact on the future of energy systems. Of the many barriers to developing DER at an urban scale, land use patterns have a great impact on
systems like district heating, where a specific building mix with specific temporal energy demands determine the viability of the system. Here, urban planning impacts the viability of certain energy systems because it determines land use patterns.
Globally, CHP accounts for under 10% of power production. In China and India, the
1
The technological advantages of CHP are outlined inthe following chapter.
percentage share of CHP could rise to 28% and 26% by respectively by 2030 (IEA 2008b).
Countries with high shares of energy production in CHP have effective policies and regulations that offer incentives to use DERs, which impacts land use at a regional and urban
scale.
1.11 Research Question
Though many studies focus on the city as an energy ecosystem (e.g. smartgrid concepts), I focus on the neighborhood scale of energy systems. This scale is important to
redevelopments that often occur in cities as a result of real estate market shifts or defunct infrastructural sites2. Redevelopment sites are typically suitable to many uses like
office, retail, academic, and medical. The use-mix of neighborhood redevelopment sites,
exemplary of larger scale land use patterns, impacts the feasibility of DERs. This thesis
answers:
.
2
121
How can urban planners and designers address energy conversion to DERs
One site in particular is New York City's Hudson Rail Yards.
at the neighborhood scale?
*
What are the impacts of altering use-mix to conform to a desired energy
profile?
" Can site-design overcome regulatory and perceptual barriers when integrating DER at the neighborhood scale?
Urban designers and planners must be able to understand the implications of energy demand on the supply systems and alternative methods to supply our cities with energy.
They are tasked with approving development proposals that impact the carbon footprint
of their cities, and are implicated in overall emissions. With DERs, planners and designers
are confronted with infrastructure siting challenges like community approval, public permitting, among others. Thus design principles discussed in this paper can serve as a guide
for the planning of distributed generation technologies for urban designers, planners and
policy makers.
The responsibility of siting power plants, electric transmission lines, refineries
and pipelines fell to planners in decades past (Andrews 2008), indicating that urban plan-
ning and design for energy systems is
hIJ
not a new concept. Urban studies have
rwAd":m
moved to model the impacts of site
design on optimized solar panel and
daylight (Compagnon 2004). Although
DERs like district heat have been popular in Scandinavia and Russia for nearly
BUSINESS AS USUAL
a century, few studies have explored
the impacts of these systems on urban
design at the neighborhood scale. The
lack of exploration is for two reasons.
(1) Development and Regulatory Landscapes I Only recently have
cities turned to DERs as a strategy for
emission reduction. Denmark has experienced remarkable growth in DERs
since it passed The Heat Supply Act in
DISTRICT HEAT
(HEAT AND POWER)
1979 (lEA 2010). In response to escalating fuel prices, Danish policy required
municipalities to create heat plans
and undergo zoning processes that al-
bwfoaMo
located buildings into heat districts
on a least-cost basis. The result is a
patchwork of neighborhood scale heat
districts, ranging from small to large
service areas as CHP plants increase in
size. See Figure 4). In the case of Denmark, public ownership of distribution
TRIGENERATION/ MICROGRID
(COOLING, HEATING, POWER)
infrastructure made this possible. However, the U.S. energy policy has sup-
ported utilities as monopolies. Utility companies own the rights to produce and distribute
heat, electric, gas, etc. These policies ensure high barriers to entry for non-utility producers of energy, thereby increasing startup , operating, and purchasing costs for DER users.
DERs atthe neighborhood scale is also prohibitive because of investment insecurity.
In the U.S., CHP appears in medical and academic campuses because they are owned
by entities with long-term investment in their real estate. However, neighborhood scale
blocks composed of individual parcels are less predictable to maintain in a system with
combined utilities and services. Therefore, transit oriented development (TOD) and mixeduse development are appropriate candidates for DER because of large, pre assembled
parcels and single landowners who are willing to make a long term investment on energy
security, fuel efficiency, and emissions reduction.
(2) Technical Inaccessibility to Planners I The existing academic literature concerning local energy conversion to distributed generation lies within the engineering and
policy realm and is not yet accessible to local planners and urban designers. The methods
for investigating DER's impacts on urban spatial patterns are elusive as atool for planning
and designing cities. I later review this literature to engage an analysis at the scale of the
neighborhood. Energy planners like Andrews (2008) recently called attention to the capacity of local action to enable DERs. Andrews frames energy systems as "flows and nodes."
He also calls attention to the capacity of local planners to expand systems beyond centralized energy production to localized nodes, or distributed generation (Andrews, 2008).
For systems such as cogeneration, Andrews suggests diversifying loads by mixing uses,
aggregating users at scales that are economically feasible, and coordinating land uses
that allow tight coupling of multiple building end-users.
Other DER studies at the intersection of public policy and urban planning analyze
urban energy patterns to find zones where load diversity can best support cogeneration
technologies (Parshall et al. 2010). Studies also examine the emissions reduction benefits
of these technologies at scales ranging from the urban district (Chen et al. 2007) to the
metro-urban area (Parshall et aL 2010). I investigate the deployment of CHP at the neighborhood scale (10 - 20 acres) as a proxy for like redevelopment sites in suitable climates.
This research benefits the argument for mixed-use developments, transit-oriented developments, and neighborhood scale energy research.3
LIV Thesis Structure
As a dual study in city planning and architecture, this thesis is organized from the
top down, beginning with the "intangibles" of policy and regulation, then to the physical
aspects of site and building planning. In Part I, I outline major challenges to the adoption
of DER at the neighborhood scale through an analysis of policy, real estate development
incentives, and issues specific to the site in Cambridge. In Part II, I review current analysis
methods for urban planning with DER, propose a novel analysis method appropriate to the
neighborhood scale, and analyze four site proposals for the Kendall Square redevelopment site. I then conduct a, sensitivity analysis is conducted to explore the interface between energy optimization, financial value, and physical form. Finally, Part Ill culminates
in a design proposal for Kendall square that incorporates the urban design guidelines and
envisions the design as a catalyst for positive change in energy behavior.
Research like "Making the Clean Energy City China" focuses on the neighborhood scale of devel3
opment as a basic unit of real estate development in Jinan, China. (Frenchman and Zegras, 2010)
What kind of cities will we build in the future? This research recognizes that an
energy-centric design process holds constant other aspect of planning such as social justice, economic development, among many others. It isthe intention of this research to answer the question few have asked: "What if neighborhood scale development were driven
by distributed energy resources?" In doing so, new questions arise concerning the role of
energy system inthe valuation of real estate development.
References:
Andrews, Clinton J. "Energy Conversion Goes Local." Journal of the American Planning Association. 74:2, (2008): 231-254. Accessed 9/4/2011. http://dx.doi.org/10.1080/01944360801993531
Chen et aL "Study on sustainable redevelopment of a densely built up area in Tokyo by introducing a distributed local energy supply system." Energy and Buildings. 40 (2008):782-792
Compagnon,R. "Solar and daylight availability in the urban fabric." Energy and Buildings. 36,
(2004): 321-328
International Energy Agency, "Cogeneration and District Energy: Sustainable Energy Technologies for Today and Tomorrow," Accessed 10/2011. http://iea.org/publications/free-new-Desc.
asp?PUBSID=2096.
International Energy Agency, "Energy Efficiency Policies and Measures: Heat Supply Act," Accessed 10/2011. http://www.iea.org/textbase/pm/?mode= pm&action =detai l&id =1212.
Parshall et aL "Spatio-temporal patterns of energy demand in New York City and implications
for cogeneration." Working paper. 2010.
World Bank, "Cities and Climate Change: An urgent agenda", 2010
181
CHAPTER 11
Site and Data Sources
This research draws from existing site plans for a redevelopment site in Kendall
Square, Cambridge, MA. Kendall Square is a business center for high tech and biotechnology companies, drawn by the proximity of the Massachusetts Institute of Technology. Stretching from the Charles River to East Cambridge (Broadway Street), Kendall
area was originally an industrial production area from the 1900's to the mid 1950's. It
then became a hub for technological innovation.
11.1 The Existing Site Plans
The existing site plans come from the real estate development studio (RED Studio)
at MIT's City Design and Development group.' These proposals satisfied a fictional request for proposals (RFP) from the land owner of the site - the MIT Investment Management Company (MITIMCO). Student teams conducted place-making studies, public
approval analysis and existing building stock analysis. Additionally the students conducted real estate market analyses for retail, hotel, commercial office, research and
development space (R&D) and market rate residential. Finally, the teams developed
several schemes; each proposal had different use-mixes, gross floor areas (GFA) and
financial values. This thesis assumes that each proposal has similar market potential
and isolates their energy profiles as a point of comparison. These results informed the
four proposals selected for evaluation in the current study presented here.
11.11 The Site Characteristics
The market analyses conducted by the students provides a key concept for under-
The studio was conducted by Professors Dennis Frenchman and Peter Roth in Spring 2010 as
1
a joint studio between the City Design and Development Group and the Center for Real Estate at MIT.
The work is credited to the four groups chosen for the experiment. Scheme 1: Adam Schwank, Chris
Wholey, Tim Canon, Jaymes Dunsmore. Scheme 2 Liz DiLorenzo, Andres Martinez, Ajay Prasad, Travis
Sheehan. Scheme 3: Neil Howard, Richard Suarez, Sung Hoon Yoon, Linyun Sun. Scheme 4: Amelia
Dolan, Alfonso Barrera-Villareal, Sam Moore, Kadija Oubala.
standing real estate demands on the site -the concept of highest and best use (HBU). HBU is
the land use and gross floor area (GFA) that has the greatest income potential at agiven point
in time. Figure 2.2 describes the site divided into zones of best use, with laboratory use along
Main Street, residential and hotel uses near the waterfront, and academic use in between.
The mock RFP includes requirements for student housing and academic space.
MIT's building stock is a hybrid of office and laboratory building typologies. The specified
baselines were 500,000 square feet of academic hybrid space and 400 graduate housing
units. If each housing unit, a mix of single, double, and triple units amount to 600 square
foot per unit, the total residential area is 240,000 square feet. Additionally, the students
were required to replace the existing GFA of any demolished buildings. Figure 2.3 explains the use-mix of the schemes proposed by the students, and shows a siteplan of
their physical form in context.
The many users of this site include abutting neighborhood groups of Cambridge, the
business community represented by the Kendall Square Association, the landowner (MIT
IMCO), and the student population.
201
The schemes address existing buildings onsite. This context raises a tension between
sustainability (embodied energy of new buildings versus preservation) and profitability of
a development proposal. All proposals chose to demolish 70% or more of the buildings because of a higher profit margin. This thesis therefore assumes that the majority of the site
would be cleared. Figure 2.2 describes the buildings on the site and the context.
The zoning and public policy context for the site includes typical restrictions on use
and height. The zoning allows for a multifamily residential, institutional and office and hotel by special permit. The existing height restrictions are at 120' and surrounding areas are
at 250', however the site already contains a 300' residential tower (Eastgate Residence)
that sets a precedent against existing restrictions. The site proposals created by student
teams met or exceeded this precedent height. Additionally, the proposals built to densities above the existing 3.0 floor area ratio (FAR), ranging from 2.5 to 5.6 FAR.
11.111 Scheme Descriptions
Each scheme is characterized by different siteplans, use mix, and financial performance. The RED Studio instructed each team to provide unique value propositions in
Scheme 1
3.7 Million Square Feet
Conference
3%
om0
Figure 2.3.1. Scheme 1.
Scheme 2
3.7 Million Square Feet
Hotel
6%
Figure 2.3.2. Scheme 2.
221
Coner
0%
4
Scheme 3
3.5 Million Square Feet
4*
4*
Figure 2.3.3. Scheme 3.
Scheme 4
4.4 Million Square Feet
Hotel
3%
/
Conference
1%
Connmdl
omce
7%
Figure 2.3.4. Scheme 4.
4If
the development. Most shared amenity traits, such as waterfront plaza, pedestrian connection to waterfront, retail corridor along Main Street, and a minor public space by the
Sloan School of Business Management. In Figure 2.3 illustrates each proposal with a pie
chart representing its use-mix.
II.IV Financial Valuation
The students used an existing financial proforma to value the projects. The proforma developed for the RED Studio accounts for building massing, construction costs,
phasing, infrastructure costs, revenues and interest. The final measure of value was
calculated as the net present value (NPV). The NPV calculates all of the cashflows from
an investment property after a certain period of time, in this case, the cashflows are
compounded annually over a 15 year period.
Floor Area (Square Feet)
Scheme 1
Scheme 2
Scheme 3
Scheme4
Academic
1,125,372
1,124,791
924,000
843,000
Commercial Office
0
123,200
219,400
304,000
R&D Lab
1,245,873
1,163,189
1,339,490
1,629,010
Retail
196,702
94,347
176,796
267,500
Total Res
821,768
992,342
734,600
1,194,300
Hotel
200,340
235,458
155,250
157,000
Conference
99,464
0
32,000
37,000
Table 2. Use-Mix of Schemes 1-4.
125
261
PART II
281
Part Il describes the relationship between CHP technology, real estate development, and policy influence that enable and bar the adoption of distributed energy resources. Key challenges to DERs lie in coordinating land use patterns that allow tight coupling of
multiple buildings and end uses (Andrews, 2008).1 The zeitgeist of Smart Growth, transitoriented development, and dense urban form become a natural candidate for the implementation of these technologies. Interestingly, the intersection of mixed use development
and energy systems has received little attention in research. Given the complex nature of
mixed-use developments, aspects of project phasing, utilization of onsite generation, and
value of emissions reduction will affect the application of systems on site. This research
is relevant to both neighborhood scale and single building developers that wish to participate in district energy systems. There are infinite potentials to power a neighborhood
scale site. Conventionally, energy planning performs the exercise of optimizing power
supply to a specific demand. This research focuses on balancing an even energy demand
throughout the day and year, without defining the specific technology - in other words, I
use a framework of optimized demand so that any implemented technology can run at its
highest capacity and fulfill the greatest amount of supply on a site.
1
The technical reasons for coupling end uses is covered later in the text.
301
Chapter III
Reconciling Demands of Real Estate and Power
Systems
111.1 Technology Description: Cogeneration of Heat and Power (CHP)
Cogeneration, described as the simultaneous production of heat and power, is
a technology widely used on corporate, academic and medical campuses. Increasingly,
downtown areas are also implementing district heating networks utilizing cogeneration.
The cogeneration of heat and power, or CHP, is a general term that may imply a building
scale or an urban scale plant. Owners can utilize building scale CHP, like microturbines,
for daytime peak load shaving or emergency backup energy.' On medical campuses CHP
is typically used to cover the entire energy demand of a site, providing superior electric
supply to that of the centralized grid. To maintain optimal efficiency of the system, CHP
can supply the constant energy demanded by a development (the base load) leaving the
peak demand (i.e. from daytime cooling) to be satisfied by centralized grid power. These
constraints determine the size of the prime mover, or the engine which converts the fuel
source into thermal or electric power.
Table 3. Description of cogeneration units by scale. Source: DOE 2009
Large CHP (>20 MW)
Mid-Size CHP (1-20 MW)
Small CHP (<1 MW)
Industrial sites, colleges
and universities, district
energy sites
High growth industrial
applications, manufacturing and assembly plants,
institutional and municipal facilities, military and
government facilities, large
commercial sites, district
Small commercial buildings,
municipal buildings, multifamily buildings, residential
buildings
energy sites
1
"Peak loads" describe the energy demand at a specific time where the distribution system experiences greatest demand. In certain energy markets, this is the most expensive energy to buy, so building
owners elect to produce energy at this time to save on high energy costs.
Cogeneration uses waste heat from the electric production process, thus providing a
high fuel efficiency by comparison to centralized electricity production, whose losses occur in production and transmission. The waste heat is useful in cold and warm climates
for building systems (i.e. space heating, domestic hot water, chilled water production, and
space cooling) because of absorption chiller technology. Andrews notes that cogeneration
is financially viable only when temporal profiles of demand for heat and power ensure high
capacity utilization (Andrews 2008). In Andrews' case, utilization describes how hard the
prime movers are running at any given time (i.e. 50% capacity, 100% capacity).
Cogeneration is a desirable alternative to centralized power production for reasons
because it has greater fuel source efficiency and it reduces losses in electricity transmission. Cogeneration provides users with reliable power quality, resilience to fuel price shifts
through bulk purchasing agreements, opportunities for peak price shaving, and serves as
an alternative to the expansion of existing power generation facilities (Peppermans et al.
2005).
111.11 Load Diversity
Important to the operation of any power plant is the concept of load diversity. Load
diversity is studied to predict maximum loads of distribution networks. For example, the
Diversity Factor is used to predict diversity of non-coincident peak demands from multiple
sources and modifies the overall peak demand predictions of distribution networks (McQueen et al. 2004) McQueen defines the diversity factor as DF,
DF=1
+ k
N
where N is the number of customers in a distribution network and k is the empirically
determined constant representing the 'diversity' of peak demands. Figure 3.1. Diversity
over daily and annual demand cycles is crucial to the efficiency of the movers (turbines)
as their efficiency returns are affected by the percentage capacity at which they run (Andrews 2008). In other words, a gas generator operating at 50% capacity may be 50% fuel
efficient whereas one operating at 100% capacity will be 85% efficient.
321
Aggregate Load Curve with Less Load Diveristy
30
A related concept, the service
25
factor, describes how much of the peak
20
demand is met with CHP. For example,
15
Resienti
a site's peak demand is 9 MW and the
--
service factor is 50%, therefore 4.5 MW
capacity is installed. However, if the
Aggregate Load Curve with High Load Diveristy
30
demand was highly diverse, your ser-
25
20~
vice factor may increase to 80%, and
you would install 7.2 MW of capacity on
10
-
-
-
-
- -
Rsidntia
site. See Figure 3.2. This means lower
carbon emissions when a site supplies
more of its base demand with a lowercarbon energy technology.
Figure 3.1. Demonstrates high (below) and low (above) load
diversity.
Production capacity, load di10 MW
versity, and district system size are
interdependent variables that determine the economic feasibility of DERs.
-Peak Demand
---
-----
--
5MW
ible
Ba
Baww
0MW
Diversity of the demand can be accom-
0
,
0
.-
r-
c_
T
r-
0 Lab 00ffice
plished by grouping diverse uses. For
example, residential buildings have a
-
Residential EHotel
Peak Demand
higher night time demand than office
-
5MW --
buildings. By grouping complimentary daytime and night time demands,
-
-
0MW
the CHP system runs at high capacity,
SLab
N Office
Residential
E Lab
N Office
Residential E Hotel
Hotel
which is directly correlated with optimum cost effectiveness. Mixed-use
10MW
development, therefore, can support
5MW
CHP systems at smaller scales because
they reduce the need for expansive, ex-
ible
OMW
Figure 3.2. Demonstrates high (below) and low (above)
service factor scenarios.
133
pensive distribution infrastructure.
111.111 Interests of the Real Estate Community
Many considerations impact the attractiveness of onsite cogeneration and distribution systems from the developers perspective. The technology is opportune for single
land owners such as university campuses. However, assembling multiple land owners requires a value proposition that challenges the security of conventional energy systems,
i.e. building-scale boiler and chiller systems. The challenge is greater when considering
the reach of large and mid-sized district systems (group building to urban district scale).
Mixed-use developments like campuses, typically have large areas of city owned or developer assembled parcels. This makes large redevelopment sites attractive for demonstrating the cost benefits and fuel efficiencies of DERs. DERs effect five phases of the development process: project initiation, feasibility studies and financing, planning and design,
construction, marketing and operational management. Though there are clear advantages
to onsite cogeneration, there is not a culture of shared utilities in private sector development.
Because financial markets and real estate markets are volatile, timing is priceless. The introduction of on-site generation may complicate permitting and construction
phases due to infrastructure site work and labor-skill gaps. Additionally, common building
systems make different site components dependent on one another for completion (Cheah
and Tan 2009). Financiers may see these interdependencies as a weakness and increase
risk assessments for projects. By reducing flexibility to change development strategy (mix
of uses, construction type) shared systems are unattractive due to perceived investment
risk.
The financial payback of a distributed generation system must include the plant,
operation & maintenance, and distribution systems (i.e. hot water/ steam piping, electrical wiring, cooling piping). When looking at a CHP system, very rarely will the financial payback look attractive if you do not include the credit associated with the space the central
plant frees up. If individual boilers and chillers are installed in a building, there is a cost
associated with the space for mechanical equipment, either as premium rooftop space or
as valuable basement space for high-tech operations. Therefore, the use of a centralized
system reduces the footprint associated with the mechanical rooms in each individual
building. Additionally, interview sources have provided rule of thumb for the cost of the
prime mover and heat recover equipment (less distributions system). These costs range
from $4,000 / kWto $2,500/kW for material and installation labor. When looking at atrigeneration system, Source0ne energy states that the addition of absorption chillers adjusts
the cost to approximately $1,400/ton for material and installed labor (SourceOne 2011).
Structuring a development team is important to a successful project. Developers,
planners and designers, financiers and public institutions need to clearly establish lines
of communication to effectively deliver real estate products (Cheah and Tan 2009). When
introducing onsite generation into a development project, experts in energy costing will
be needed to advise costs and implementation strategies. The introduction of more team
members may be perceived as a negative to the developer's project fee, equity stakes, and
timing of planning process.
Marketing concerns for real estate developments vary between tenants' perspective, transient users like shoppers, and other consumers that drive value in real estate. A
development using cogeneration may receive marketing benefits because the GHG emissions are lower than others using grid power and building scale heating (Allane and Sari
2004). Many policy barriers exist before these benefits can be seen, such as the differentiation off the localized vs global carbon emissions produced by onsite generation (IEA/
OECD 2009). Schemes like the Tokyo Cap and Trade system promise incremental revenue
gains from lower emissions buildings in commercial and industrial sectors (Nishida and
Hua 2011). However, recent trends in saturated carbon markets reduce the impacts of
penalization from these schemes, thus disincentivising participation in emissions reductions efforts (Coelho 2011).
From the perspective of an incoming building owner or tenant, power reliability and
connection cost will be considered. Additionally, certain building types require heightened
power security, like hospitals and laboratory buildings. These tenants can satisfy their
required alternative power supply in case of a grid brown out.
Real estate development optimizes the highest-best use of a site
(HBU). HBU is the use and floor area that
has the greatest income potential at a
given point in time. It is sometimes unclear what the appropriate mix is, therefore, energy planning can provide one (of
many) determining factors to use-mix.
Ill.IV Potential Conflicts of Use-Mix
To enable DERs at the neighborhood scale, planning and design communities should plan for diverse energy
demand, couple energy users early in development stages, and design the phasing process accordingly.
Neighborhood
scale
develop-
ments have the opportunity to service
their entire energy needs through cleanFigure 3.4. The energy diagrams (right) show possible energy supply plans over time.
er technologies like CHP. The previously
discussed concept of 'service factor' is
enabled by diverse energy demand. Diversity is achieved through the aggregate
demand of many uses. However, uses
can be inflexible given the Highest and
Best Use of a site and the intention of
maximizing profit. Additionally, the HBU
changes over time in either density or use
(Eichholtz and Geltner 2002). This thesis
explores the tension between energy di-
Figure 3.3. Illustration of development phasing plans. Above, the plans have a centralized plant. Below, the
plans have distributed plants for each parcel or building.
versity and use-mix, to reconcile both agendas of profitability and emissions reduction
can be met.
As Cheah and Tan mention, common building systems make each phase dependent on the next, which means phasing can either enable or complicate the implementation of DERs. Figure 3.4 describes the phasing process for the proposed Kendall Square
schemes. The figure demonstrates that developing adjacent parcels will maximize the utilization of generated power. The Kendall Square schemes are envisioned to develop over a
15 year timeline in four phases. Figure 3.4 shows two scenarios, using building scale units
that connect through a micro-grid system (dotted ines) and by incrementally adding generators in a central, modular system.
REFERENCES:
Allane and Sari. "Distributed energy generation and sustainable development." Renewable and
Sustainable Energy Reviews. 10 (2006): 539-558
Andrews, Clinton J. "Energy Conversion Goes Local." Journal of the American Planning Association. 74:2, (2008): 231-254. Accessed 9/4/2011. http://dx.doi.org/1 0.1080/01944360801993531
Cheah and Tan. "Mixed-use Project Development Process: Features, Pitfalls and Comparisons
with Single-Use Projects." 2009. Accessed 10/19/2011. http://www.people-x.com/homepage/
iccem-iccpm/data/ICCEM-ICCPMFullPaperSample.pdf
Coelho, Henderson and Neely. "U.N. Carbon prices tumble to new record lows." Reuters Online.
Accessed 12/14/2011. http://www.reuters.com/article/2011/1 2/1 4/us-carbon-market-pricesidUSTRE7BDORN20111214
Eichholtz and Geltner. "Four Centuries of Location Value: Implications for Real Estate Capital Gain in Central Places." Accessed 12/25/2011. http://web.mit.edu/cre/research/papers/
wp86eichholtz.pdf
King, Douglas E. "Electric Power Micro-grids: Opportunities and Challenges for an Emerging
Distributed Energy Architecture." doctoral dissertation, Carnegie Mellon University, 2006.
McQueen et aL "Monte Carlo Simulation of Residential Electricity Demand for Forecasting
Maximum Demand on Distribution Networks." IEEE Transactions on Power Systems. 19:4
(2004):1685-1689.
Nishida and Hua. "Motivating stakeholders to deliver change: Tokyo's Cap-and-Trade Program."
Building Research & Information. 39:5 (2011): 518-533
Peppermans et aL "Distributed Generation: definition, benefits and issues." Energy Policy. 33
(2005): 787-798.
381
Sean Selha. (Director of Energy Systems, SourceOne Energy Solutions) in discussion with the
author, December 2011.
40
Chapter IV
National and Local Policies and Barriers
IV.l Overall Barriers
Although clear benefits can be seen from these systems, the concept lacks commercial attention in the United States. King notes that the slow adoption of DERs can be
attributed to technical challenges, lack of 'turn-key' implementations, real and perceived
risks of micro-grid systems, and the resistance to new entrants into the energy market by
power utilities. The value of DERs can be greatly improved by aggregating and interconnection small groups of customers onto a local grid. The micro-grid concept is advantageous because of increased levels of reliability, greater end-use fuel efficiency through
the use of combined-heat-and-power applications, redundancy, and possible economies
of scale (King 2006).
IV.I Policy Enabling Widespread DER's
Among all countries with successful CHP markets, there has been focused government policy on heating and electricity supply (IEA 2008). The US DOE began promoting CHP after the 1970's fuel crisis as a means of greater fuel utilization efficiency. Since
utility market deregulation, large scale CHP systems (connected through district energy
systems) have had access to sell power back into the grid. Additionally, the EPA recently
released for comment a draft "output based emissions standard" that proposes emissions
limitations of power plants based on the combined useful output of electricity and thermal
energy (IDEA 2005). This differs from current standards that cap emissions limits based on
emissions content of fuel input to the plant.
The DOE has supported Clean Energy Application Centers (CEAC's) that promote
the expansion of CHP waste heat recover and district heating technologies. The CEAC's
have collectively supported more than 350 projects, representing 1.3 GW of installed CHP
power. Their research has been focused on market transformation, developing market as-
sessments for all types of building types and development sites (DOE 2009).
IV.lI Barriers for DERs and Developments
A major problem identified by the International Energy Agency's report on CHP is
that interconnection measures between CHP electricity and the utility grid is typically unclear and inconsistent. The Energy Policy Act (EPA) of 2005 established the US's interconnection standards to which utilities must adhere. Most of these policies use state guided
measures of interconnection, therefore, national vendors have a more difficult time than
if the system required nationalized standards.
Additionally, interconnection barriers are set by regulations on infrastructure expansion. For example in Massachusetts, crossing a public right of way with an electricity
infrastructure constitutes the producer as a utility. I an interview with Patrick Haswell
of Veolia Cambridge, he noted this prohibitive regulation as a high barrier to entry at the
neighborhood scale.
Other political boundaries include difficulty in securing fair value prices for cheap
electricity that is exported to the grid. Massachusetts has attempted to ameliorate this
with The Massachusetts Alternative Energy Portfolio Standard (APS) supports non-RE
technologies (flywheels, gasification, CHP) in electric and thermal production. The Alternative Compliance Payment (ACP) Rate is $20/MWh and increases with CPI. For example,
the DOER shows a 500kW system generating $87,500 in revenues per year.
Other policies like the 1999 N.J. State Ordinance 48:3-51 exempts producers from
regulated electricity sales by on-site generation facilities to "contiguous" end users which
includes customers separated by an easement. Additionally, in 2007, the Burrstone energy Center determined that cogeneration facilities we permitted to distribute energy to
multiple end users and that the facility's distribution lines were permitted to cross public
streets in order to do so.
IV.IIl.1 Ownership Structures
Cogeneration has seen an array of ownership models in the United States. In paral-
421
lel with the distribution system, the production facilities are either municipally owned or
treated as private utilities. Profitability, plant desirability and energy demand determine
the viability of the systems. As in the case of Cambridge, MA, Veolia Energy owns steam
distribution infrastructure while Mirant / Southern Energy owns the production system.
Other cities have taken ownership of the systems, by forming municipal utilities and nonprofits, after they have become unprofitable for utilities to operate.
IV.IV Promoting DERs
IV.IV.I Municipal Level Mandate Approaches
Policy mechanisms such as infrastructure and heat-planning can bring swift
adoption and conversion of distributed generation like CHP. Denmark's Heat and Electricity Planning is the extreme example of policy mandates enabling CHP. Though a national
policy, it is applauded for its emphasis on local government action. The First Heat Supply
Law was introduced in 1979, requiring municipalities to carry out studies on the potential
for district heating (DH) in their jurisdictions. The policy success has led Denmark to become a world leader in CHP, seeing fuel savings of 290000 tonnes of oil equivalent (toe)
per year over individual heating. The regulation guaranteed head and electric markets to
increase the commercial viability of CHP/DHC.
The role of government, its regulatory power of production and distribution systems, is paramount in a step change like full scale CHP conversion. The scalability of
Denmark's heat and electricity planning to a municipality like Cambridge is questionable,
given the ownership of the production and distribution systems of domestic energy. However, the question begs to be asked, what controls such as zoning and permitting can be
used to enforce adoption of distributed generation?
When the borough of Merton wanted to incentivize emissions reduction, it successful spurred the introduction of CHP technology. The Merton Rule, introduced by the
London Borough of Merton in 2003, was enacted to reduce emissions from the building
scale. It supports energy efficiency and renewable technologies by requiring a ten percent
emissions reduction for all new structures in the borough. The Merton Rule illustrates an
effective way to introduce both renewable generation and energy efficiency. Its success is
attributed to the coordinated approach between Merton and building developers though
clear guidance and municipal advice. The rule lead to the adoption of similar initiatives by
cities across the UK and creation of demand for renewable energy, efficiency and small
scale CHP.
IV.IV.lI Municipal Incentive Approaches:
In Trenton, New Jersey, the city is embracing the state Board of Public Utilities
"Pay for Performance Program". The goal of the program is to reduce energy use in buildings by 15%. Additionally, there is a maximum $1 million dollar incentive package for the
installation and operation of CHP units in new and existing buildings. The program takes
the form of capacity building, using consultants to perform and energy audit. The facilities
must upgrade and subsequently commission the efficiency of their systems. No reports
exist on the success of CHP installation as a result.
Additionally, Trenton has led by example. Contracting with Trigen Energy Corporation, the City of Trenton successfully reduced their operations and maintenance costs by
removing their building scale boilers and chillers and switching to a district energy system
provided by a cogeneration facility. A 12 MW system, 31 buildings are serves by the heat
and chillers and the electricity is treated as a by product sold back into the grid.
IV.IV.Ill Educator and Communicator- Building Capacity
The city of Frankfurt supported CHP deployment with two offices in the city. One
office, named Energiereferat in 1989, is responsible for suitability analyses and a clearing
house for consumer and utility communications. The second office, named BHKW Arbeitsgruppe in 1991, was responsible for energy supplier communications to standardize
installation and planning procedures. Frankfurt connected local energy suppliers (such
as Mainova AG and SUWAG MKM AG) to consumers, the suppliers providing technical and
financial support. The benefits included gas price discounts, installation grants, long term
payback financing, and an attractive electricity buyback structure (through the Ststwik
STVV electric utility). From 1991 to 2007, this strategy yielded 120 CHP systems running
at MW and 11 DHC networks totally 150 kilometers (km). Consumer savings, emissions
reductions and job creation were all benefits. The success has been attributed to a sense
of political ownership and infrastructure standardization.
IV.IV DERs in Cambridge Policy
This thesis uses Kendall Square, in Cambridge, MA as a planning exercise in Part
II. This section outlines important regulatory, political, and physical characteristics of the
locale that impact the success of DERs.
The City of Cambridge has served as an educator and led by example to reduce
emissions. The city's climate action plan uses GHG emissions reduction as its primary
measure of success, noting natural gas as a transition fuel and that "future energy system should better enable the community to adapt to impacts and to changes in energy
availability". The Climate Action Plan notes, "using less energy means achieving higher efficiency- accomplishing the same task with a lower amount of energy." Cambridge's Plan
encourages building owners to use an existing district heat system. This 5 mile system
currently supports 15 large customers at 240,000 lbs/hr of steam production capacity.
Specifically, the City wants to increase steam use by way of other customers by 200 million pounds annually.
IV.V Potentials of Zoning
The City of Cambridge Zoning has precedence for both CHP and wind power, given
their experience with the MIT, Harvard and Veolia CHP plants. This is important because
dated zoning codes can be prohibitive to alternative energy technologies. However, there
is little involvement in the discussion or promotion of energy through zoning. The specialized amendments to Cambridge's Zoning aren't geared towards wide-spread adoption of
CHP, in other words, CHP is not allowed by-right in many places.'
For example, Ordinance 17.402 identifies the only by-right space for utilities in the
city, located at the Harvard cogeneration plant between Cambridgeport and Harvard area.
Thus, CHP plants are not permitted in Industrial zones, where the benefits of waste-heat
may be most useful. Areas like those North of Camrbridge St. have a high concentration
The term 'by-right' describes the allowable functions in zoning code. For example, the building
1
height limitation of a district may be 150' by-right. Any alterations must be submitted for approval.
46|
of industrial uses adjacent to high density neighborhoods. With this adjacency of uses,
heat demand may be spread evenly throughout the day and cogeneration would be highly
attractive.
The City of Cambridge has educational support for GHG emissions reductions by
initiating the Cambridge Energy Alliance, which supports energy efficiency measures with
residents and businesses in the Cambridge Area. This non-profit was initiated by the city
to meet the growing need of energy efficiency education and outreach.
Although municipalities frequently update their zoning, The City of Cambridge has
a unique opportunity to reframe the energy agenda for one of its economic cores, Kendall
Square. The city is initiating a zoning studying for the Central Square and Kendall Square
areas, including a 'transition zone' between. There are three large districts that are to be
rezoned, providing an opportunity for catalyst projects to demonstrate the City's capacity
to regulate/inform energy planning.
Figure 4.3. Potential
sizes for energy overlay districts.
IV.IV Problems for DER at the Neighborhood Scale
To enable DERs at the neighborhood scale, planning and design communities
should plan for diverse energy demand, couple energy users early in development stages,
and design the phasing process accordingly.
Integrating district systems in early design phases can decrease prohibitive infrastructure siting problems like crossing public right of ways and appropriately developing
the phasing plan. Planners and designers can minimize the complications associated with
crossing beneath public right of ways by inventively handling the expansion of infrastructure. This may require transferring public right-of-ways to a land owner (a questionably
feasible option), or bridgingthe right of way with wiring, heating and cooling infrastructure.
Robust 'heat planning'and emissions incentives have proven to increase CHP share
of overall energy delivered in countries with high heat demand, however, with the advent of
absorption chilling technology, the district concept is not relegated to cold climates. Domestic 'heat planning' could be conducted through overlay zoning, a zoning methodology
to regulate environmental and economic factors through land use, resource consumption,
building form, and incentives.
Energy Overlay zones require an intimate understanding of the energy load-land
use relationship. The Parshall et al. study has many components of such a study. However,
overlay districts are projective. Where the Parshall et al. study identifies zones of demand
suitable to CHP, an Energy Overlay districts would identify where they could work, the size
of the system, and the overall emissions reductions desired.
REFERENCES:
City of Cambridge. Climate Change Protection Plan: Local Actions to Reduce Greenhouse Gas
Emissions. Accessed 10/2011. Http://www2.cambridgema.gov/cdd/et/climate/clim-plan/clim_
planfulL.pdf
International Energy Agency (IEA). Cogeneration and District Energy. IEA/OECD: Paris, 2009.
Industrial Technologies Program, U.S. Department of Energy. Combined Heat and Power: A
Decade of Progress. 2009. Accessed 10/4/2011. http://www1.eere.energy.gov/industry/distributedenergy/pdfs/chp-accomplishments-booklet.pdf
King, Douglas E. "Electric Power Micro-grids: Opportunities and Challenges for an Emerging
Distributed Energy Architecture." doctoral dissertation, Carnegie Mellon University, 2006.
501
151
521
Part III
54
In Part III, I investigate the impacts of optimizing energy demand by use-mix. Section 1
outlines existing literature that tests the deployment of DERs at neighborhood and urban
scales. In Section 2, I examine the development site, Kendall Square, in terms of use-mix
and energy. This exercise combines energy use data with site scale program information
to reveal which scheme has the greatest load diversity. Additionally, I draw conclusions
about the use-mixes most conducive to DERs. Section 3 is an exercise that attempts to
optimize use-mix to achieve the highest load diversity. I perform a sensitivity analysis on
use-mix and test its impacts on energy demand, financial valuation, and physical form.
Part 11concludes with lessons about use-mix optimization.
b6 I
Chapter V
Analysis of Existing Schemes
V.1
Literature Review
The conversion of energy systems has received a great deal of attention from the
municipal planning, policy and engineering communities. Studies have focused on policy, engineering and site identification of DERs. Parshall et al. give an extensive review of
models testing the suitability of cogeneration in varied scenarios. The research community
addresses cogeneration-oriented annual building load modeling (ORNL 2009), GIS models
linking simulated building loads to determine excess heat to mitigate urban heat island effect (Dahkal et aL., 2002; Heipel and Sailor, 2008). This research builds on the philosophy of
the Community Energy Management framework, where benefits of particular energy systems are examined at the community level (Yamaguchi, 2007).
Parshall et al. demonstrate the energy demand profiles of New York City's average
daily use. The study identifies space heating, space cooling, hot water and basic electric as
components of energy demand. As a consideration for space availability in urban environments, the study addresses space to host a generator by identifying an 'anchor building'
that has a footprint of 2500m 2 or more. They identify a base case against which they measure emissions savings via data from the City of New York, including percentages of heat
met with varied fuel sources, chiller efficiencies, and electric transmission/distribution
losses. Assuming no financial restraints, the study proposes that single cycle micro-turbines are the most appropriate technology at the block scale. The study assumes that the
scenarios are thermal load following, meaning the amount of electricity produced depends
on thermal demand. The study notes that their model neglects the inclusion of emissions
savings from buildings on existing district steam systems.
Studies have also attempted to quantify the amount increase in energy efficiency
and/or emissions abated due to cogeneration. Astudy of sustainable redevelopment strat-
egies in Tokyo's Sancha District not only developed a future scenario for district energy
demands, but modeled appropriate systems for districts and tested the effects on carbon
emissions. Additionally, they tested the effects of waste heat on urban heat islands to
identify the connection between pedestrian comfort and DER (Chen et aL. 2007). The study
justified the placement of these systems in urban contexts by arguing that the building
stock turnover provides the opportunity for alternative energy systems, facilitate infrastructural expansion, and building upgrade. Chen et aL. subdivide a large region of Tokyo
into districts by natural groupings of like building stock. They deploy a myriad of energy
solutions such as cogeneration, hydrogen fuel cells and solar PV. Though it is not clearly
stated, I assume that their building data was achieved via simulation. Their per building
demand was calculated via floor area from GIS database. The primary results compared
the percentage of energy produce by DER and the carbon emissions abated against a base
case scenario.
V.1.1 Technology Costs
At the group building scale, the supply efficiency and cost effectiveness of DER is
dependent on when the buildings are occupied, or occupancy schedules. These occupancy
schedules dictate energy demand and are typically expressing on an energy per unit area
demand, like watts per square foot (W/ft2). The district energy simulation model by Yamaguchi et al. (2003) provides a model for summing the input and output of energy in groups
of buildings by applying building energy simulation on a per floor area basis. This study
then tests the efficiency of in- building CHP units versus a centralized CHP system.
In a single or group building scenario, urban planners are often faced with a cost
analysis that compares a business as usual mechanical system with a DER option. Although it is not within the scope to test, I argue that in addition to regulatory powers shifting energy planning paradigms, it is building owners and real estate developers that enable DER's like cogeneration via comprehensive understanding of cost benefits provided
by the system. Both the ORNL-BCHM and Yamaguchi et aL. (2003) models test the cost
effectiveness of DER systems in context. Yamaguchi et aL. test simple payback periods
581
and asset depreciation as compared with efficiency of different systems.
V.1.11 Load Diversity
I look at load diversity as a driver of development decisions, attempting to achieve
the greatest diversity of loads. Where many studies use the diversity factor as an input of
given energy behavior, this study focuses on maximizing the benefits of high load diversity
at the neighborhood scale of development.
Key to these studies is an understanding of building energy performance and aggregating that information for groups of buildings. The cooling, heating and electrical systems create a load profile for a building, or a group of buildings over time. Chow et al. applied genetic algorithm (GA) to optimize district cooling system efficiency (DCS) through
a gross floor area (GFA) optimization (Chow et al. 2004). GA is beneficial in this sense because it analyzes many variables in parallel, as opposed to a point based search method,
in which only a single point is evaluated at one time. For example, the experiment done by
Chow et aL defines a diversity factor to achieve and allows all uses (office, retail, residential, hotel, transit) to vary infinitely. In the case of Kendall Square redevelopment, there
are anchor uses like Academic space and Residential space required by the land owner, on
to which others (like lab) are added for economic value. Future studies of load optimization should incorporate anchor uses to address the natural tension between optimization
exercises and demands of real estate markets.
V.AI
Lessons from the Initial Development Schemes
V.11.1 - Explaining The Data Sources And Characteristics
To address the need for an analysis methodology of neighborhood scale site evaluation favoring DER's, I use four site proposals from a real estate development studio (RED
Studio) at MIT's City Design and Development group.1 These proposals satisfied a mock
1
The studio was conducted by Professors Dennis Frenchman and Peter Roth inSpring 2010 as a
joint studio between the City Design and Development Group and the Center for Real Estate. The work
is credited to the four groups chosen for the experiment. Scheme 1: Adam Schwank, Chris Wholey, Tim
Canon, Jaymes Dunsmore. Scheme 2 Liz DiLorenzo, Andres Martinez, Ajay Prasad, Travis Sheehan. Scheme
3: Neil Howard, Richard Suarez, Sung Hoon Yoon, Linyun Sun. Scheme 4: Amelia Dolan, Alfonso Barrera-
request for proposals (RFP) from the land owner of the site tt the MIT Investment Management Company (MITIMCO) Student teams performed place-making studies, public approval analysis and existing building stock analysis. Additionally the students conducted
real estate market analyses for retail, hotel, commercial office, research and development
space (R&D) and market rate residential. Finally, several schemes were developed from
groups of designer-developer teams. Each proposal had different use-mixes, total gross
floor areas (GFA) and financial values. This thesis assumes that each proposal has similar
market potential and isolates their energy profiles as a point of comparison. These results
informed the four proposals selected for evaluation under this study.
The development brief includes requirements for student housing and academic
space, which is assumed to be hybrid office and laboratory building typologies. The specified baselines were 500,000 square feet of academic hybrid space and 400 graduate housing units. If each housing unit, a mix of single, double, and triple units amount to 600 square
foot per unit, the total residential area is 240,000 square feet. Additionally, the students
were required to replace the existing GFA of any demolished buildings. Figure X explains
the use-mix of the sites, and shows a siteplan of their physical form in context.
V.11.11 - Energy Profiles and Assumption
Energy load profiles were created by modeling like buildings in DesignBuilder, an
interface of EnergyPlus building modeling software. Hotel, office, residential, and laboratory buildings yielded annual, weekly, and hourly energy demand.2 Demands from different building systems were considered such as domestic hot water, electric, cooling and
heating.
Villareal, Sam Moore, Kadija Oubala.
Although occupancy between commercial and academic building types would realistically vary, the
2
model used a single occupancy schedule for each building type. Given the non-standard operation on MIT's
academic buildings, this may skew the results to not represent certain nighttime loads.
After individual buildings were modeled in DesignBuilder, the load profiles were aggregated to get a 'gross
site demand' for heating and electric loads. (This represented the development in a fully built scenario,
understanding the assumption is a fully operational system in the future.) To find maximum demand of the
system, I use weekly load profiles from the summer and winter 'design weeks'. These are the weeks of the
year used to size HVAC systems in a business as usual scenario. I use the 'design weeks' to see the upper
limits of demand on the supply because the waste heat from cogeneration directly effects the availability of
energy.
601
The test operates under the assumption that each use mix is suitable to the site
and will remain the same for the life of the development. However, changing market demands may compromise initial uses of the site, negatively affecting the economic feasibility of the system. Large systems are at greater risk of use changes and technological
substitution. This affects system feasibility at the block and city scale alike. For example,
the Kendall steam system operated by Veolia energy) seeks users to utilize the excess
steam they produce on a daily basis (Veolia 2010).
V.11.111 - Methodology
The analysis is designed to reveal the load diversity of each given proposal. The
following steps were taken to analyze the load diversity of each scheme:
1 Simulate individual buildings by use on a per area basis (Figure 5)
2 Aggregate demand by floor area for four site proposals (Figure 5.1)
3 Analyze the evenness of the curve by standard deviation test
4 Evaluate proposals
Energy demand is derived by the use of building simulation software DesignBuilder. An industry standard for building simulation, DesignBuilder uses the DOE-developed
EnergyPlus platform as a basis for calculating thermal properties in buildings over time,
providing mock occupancy schedule and building skins as baseline that meet national
building standards ( i.e. ASHRAE 90.1). I identify four building uses from the study and
use predefined occupancy schedules, mechanical systems including elevators, lighting
controls, and a highly insulated building cladding system (UValue = .25) as inputs for the
simulation. The building types are divided into laboratory, hotel, residential, and office.
These demand profiles were aggregated into total electric and heating demands
for each building type in energy use per floor area (kWh/m2). When all loads are aggregated, the total site energy profile can be tested for its load diversity. The four site schemes
show a high peak demand during the daytime, maxing out at approximately 18 MW of peak
demand on the harshest week of summer. Referring to Figure 5, one can see the daytime
dominant loads are in the office and laboratory uses.
I simplify the building energy demand data into heat and electric demand. The typical outputs from the building simulation describe total electric and total gas consumption
in kWh/m2. By utilizing absorption chiller technology, the energy used by electric chillers
for space cooling can be accounted for in the heat demand. This was incorporated into the
energy simulation within DesignBuilder's mechanical equipment options.
After aggregated, the gross energy loads of the site are tested for diversity. I perform a standard deviation analysis of the data over the course of the design weeks for all
four schemes. Using standard deviation, the lowest possible load diversity would be represented by the score 0. This tests the fluctuation above the base load, not a magnitude of
energy use (i.e. units MW) The Lower the standard deviation, the higher capacity daily basis.
To represent the annual behavior of the loads, I average the standard deviations from the
winter and the summer design week to get an annual 'evenness' factor.
621
V.II.IV Results
Using standard deviation, the lowest possible load diversity would be represented
by the score 0. The results show a load diversity ranging from 4.2 to 2.1 on a seasonal basis. See Table 5. Given the small variation in use-mix among the schemes, a 200% variation in toad diversity is significant. This indicates that the Schemes 1 and 2 have a higher
service factor than Scheme 3 and 4. From an energy planning perspective, these schemes
are most desirable.
On an area basis, Schemes 1 and 2 have many trends common per their use-mix.
See Figure 5.2. Among the sample, the two schemes represent the lowest commercial office, middle range residential, highest hotel, lowest in R&D Lab, and highest in academic
office. On a percentage basis, the two schemes exhibit the lowest R&D Laboratory, lowest
commercial office and highest academic office. [See figure] There is a correlation between
the high percentage of hotel/residential and the nighttime loads needed to maintain an
even distribution over the diurnal loads.
V.I.V Discussion
The schemes with a higher diversity in uses, particularly higher hotel and residential, better supports feasibility of cogeneration systems at the neighborhood scale. Cogeneration systems with district level distribution are historically larger than the proposal
site. Because the diversity factor only reached 2.1, 0 being optimized, one may seek a higher load diversity. Seeking higher load diversity may be accomplished in one of two ways.
The first option is to expand the distribution infrastructure, in this scenario, to neighboring residences or hotels to the North. Given the proximity of neighboring district steam
systems in MIT and Kendall, the infrastructure could attach itself into the larger network
in the Cambridge area. The second option would be reducing daytime loads or increasing
nighttime loads on site. This can be accomplished by adjusting existing program or by adding additional uses. Additional uses may include thermal sinks like production facilities
(i.e. micro-chip processing, small manufacturing) that operate primarily at night. Specific
to the test site, such a facility would only be feasible if it occupied low-value space, produced little noise and air pollution. For DERs spread over larger areas, the chance of adjacent complimentary uses between light manufacturing and residences would increase.
641
Percentage Floor Area by Use
40%
-
- - - -
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Schem
e1
Scheme 2
30%
Scheme 3
---
10%
-
Scheme 4
- -
--
0%4
Academic
-
--
Commercial
Office
R&D Lab
Retail
-
-
Total Res
Hotel
Conference
Figure 5.2. Comparison of schemes by floor area distribution.
Design Proposal
Scheme 1
Scheme 2
Scheme 3
Scheme 4
Electric
Heat
Electric
Heat
Electric
Heat
Electric
Heat
IStandard Deviation of Load Capacity over Design Weeks
Winter
Summer
2.4
3.0
2.1
2.3
2.4
2.9
2.8
3.4
3.5
4.2
2.1
2.3
2.5
2.9
3.1
3.5
Table 5. Comparison of schemes by floor area distribution.
Mean
2.25
2.65
2.25
2.6
2.65
3.15
3.3
3.84
S/W Mean
2.45
2.425
2.9
3.57
References:
Chen et aL "Study on sustainable redevelopment of a densely built up area in Tokyo by introducing a
distributed local energy supply system." Energy and Buildings. 40 (2008):782-792
Chow et aL "Building-mix optimization in district-cooling system implementation." Applied Energy.
77:1 (2004): 1-13
Dhakal and Hanaki. Improvement of urban thermal environment by managing heat discharge sources and surface modification in Tokyo. Energy and Buildings, 34:1 (2002): 13-23.
Harvey, Low Energy Buildings and District Energy Systems. (London: Earthscan, 2006), 572.
Heiple and Sailor. Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles. Energy and Buildings. 40 (2008)
1426-1436.
Oak Ridge National Laboratory, 2006. ORNL CHP Capacity Optimizer. Accessed 11/2011. http://
appsl.eere.energy.gov/buildings/tools-directory/software.cfm/ID=495/pagename=alpha-tist
Parshall et aL. "Spatio-temporal patterns of energy demand in New York City and implications for
cogeneration." Working paper. 2010.
Veolia Energy. "Green Steam- An Urban Solution." http://files.eesi.org/dicroce_092311.pdf
Yamaguchi et aL "Development of district energy system simulation model based on detailed energy demand model." Eighth International lBPSA Conference.7/11-14/2003.
Yamaguchi et al "Proposal of a modeling approach considering urban form for evaluation of city
level energy management." Energy and Buildings, 39:5 (2007): 580-592.
661
67
681
Chapter VI
Optimizing the Scheme
In this chapter, I perform a sensitivity analysis of use-mix on Scheme 1 to further
explore the spatial quality of the site, aggregate energy load diversity, and assess financial
feasibility. Financial feasibility is measured using the RED Studio mixed use proforma and
the net present value of energy cost savings. This analysis also defines the benefitsgap in
designing a site for energy. The benefitsgap indicates how much payoff is needed from the
DE system to provide an equally attractive investment opportunity to that of the baseline
scenario - that is 100% lab use.
VI.I Research Goals
I reviewed the impacts of cogeneration on project revenue in large
In an Chapter 111,
developments. Of the many factors, I test here the effects of use-mix on the financial valuation of the project, expressed bythe Net Present Value (NPV), the sum of all project cashflows which are discounted by interest over a fifteen year period. My research goals are to:
*
Link the effects of load diversity optimization to site layout and profitability
*
Explore the trade-offs made when redistributing use-mix in views, solar access,
etc.
Hypothesis: A use-mix with high load diversity, meeting the minimum development
requirements, can also result in a high quality development with attractive public
space, views, etc.
II.III.I Methodology
Space Redistribution I Given the dominant contribution to daytime energy demand
and dominant percentage of use area in each scheme, I choose to test the lab use as a
proxy for adjusting use-mix in favor of load diversity. One way would be to add more use
area with nighttime demand, such as residential and hotel. The site, however, is consid-
ered to be built to maximum capacity. Therefore, I propose subtracting use area from the
daytime dominant load uses (lab).
To control the experiment, I propose a set of control floor area rules that build
on the scheme that demonstrates the best load diversity. After stating the controls, the
daytime dominant uses will be varied in 25% increments to observe step changes in load
optimization. See Table 6.
Financial Analysis Tools I Using the existing financial proforma from Scheme 1, I
examine the effects of use-mix changes on the NPV. The proforma developed for the RED
Studio, described in Chapter II, accounts for building massing, construction costs, phasing, infrastructure costs, revenues and interest. This experiment assumes that building
massing changes slightly, but not enough to effect construction costs since the total floor
area is maintained in each version of the sensitivity analysis. Energy cost savings are another indicator of financial performance as the load diversity increases over the range of
scenarios. Using a Discounted Cash Flow (DCF) method, I calculate savings over a fifteen
year period for each scenario, in-step with the overall NPV. The energy cost savings show
how scenarios with greater utilization of DERs benefit from lower cost per unit of energy.
To calculate these savings, my control inputs include total energy demand of the
winter and summer design weeks, price per unit energy in both conventional and district
systems, and an inflation rate for discounting the savings over time. The variable input is
the ratio of DER supplied energy to conventionally supplied energy. The price per unit energy is assumed to be an average of peak versus non-peak pricing and accounts for variation in monthly pricing. These figures are taken from a DER feasibility study conducted in
the Hudson Yards district of New York City. (See Appendix A). The base loads are priced at
DER supplied energy rates and the non-base loads are priced at market energy rates. Total
energy demand is divided into electric (MWh) and heat loads (therms), divided into base
and non-base loads, and multiplied by the respective energy rate.
Design Modeling I The impact of GFA redistribution can be observed on the physical quality of the site by keeping total floor area constant among optimization tests. To
demonstrate the impact of redistributing the uses, I redesign the site for each sensitivity
Process
Identify Desired Load Shifts
H0
Existing Aggregate Energy Profiles,
Load Diversity Calculations
Use-Mix Studies
Load Diversity Sensitivity Analysis
Financial Feasibility Analysis
H411
Mixed-Use Proforma
H
Quality of Space Analysis
Development Recommendations
Tools
Massing Studies
Development Guidelines, Design Guidelines, Policy Incentives
Figure 6. Process of sensitivity analysis.
Floor Area By Use with 25% Increment Reduction inLab Area
Academic
Commercial Office
R&D Lab
Retail
Total Res
Hotel
Conference
TOTAL
75%
50%
25%
0%
1,268,812
0
934,405
221,774
926,511
225,875
112,142
3,689,519
1,412,253
0
622,937
246,845
1,031,254
251,411
124,819
3,689,519
1,555,693
0
311,468
271,917
1,135,997
276,946
137,497
3,689,519
1,699,134
0
0
296,989
1,240,740
302,482
150,175
3,689,519
Table 6. Floor area breakdowns
analysis. Leaving the initial design principles constant ( e.g. pedestrian circulation, general
building footprints) I redistribute the building massing for each iteration to maximize daylight
and views. Tools like the Urban Modeling Index (UMI)l simulate the comprehensive effects
Recently developed at Harvard Graduate School of Design, the Urban Modeling Index (UMI) is a site
1
scale simulation tool intended for urban designers to test end use consumption of urban scale configurations.
Based on the Energy Plus platform developed by the U.S. Department of Energy, UMI applies detailed energy
simulation at the building scale to urban scale models. This program provides accurate simulation of internal
loads (occupancy, equipment, use), external loads (climate), solar gains, shading reflection, thermal mass,
building form and construction, and photovoltaic panels. UMI does not currently simulate urban heat island ef-
Figure 6.0.1. Schematic of methodology and tools.
Use Mix of
Scheme 1 Scenario 2
(i.e. 50% of Original
R&D Lab Floor Area)
Building
Categonzation
Program
Categorization
Program
Categorization
Typical Building
Footprnt, Floor Area
Typical Building
Footprint. Floor Area
&Construction Type
Site Guidelines,
Circulation. Public
Space. Views
& Occtpancy S~ed.ai
HVAC,Building SIdn
Specification
1
Typical Building
Hourly Weather Data
Footprnt, Floor Area
& Occupancy thed.at.
Phases of Constuctlon+ Cashtlow Analysis 4-Deal Structure, Cap Rate
Assumptions, RentNacancy
Asssumptons
Overall Site Layout
Daylight Gains
Solar Access/
Pedestrian C
Summer and Winter Design Week
Load Datalase (W/tt) for Each Building Type
Aggregate Load Demand For Site
1
Energy Analysis
Net Present Value of Development,
Internal Rate of Retum,
Residual Land Value
O
If
Load Diversity Factor
Overil Prttblity of Project
Profile of
Scheme I Scenario 1
(i.e. 25% of Original
R&D Lab Floor Area)
Profile of
Scheme 1 Scenario 2
(i.e. 50% of Original
R&D Lab Floor Area)
Site Scale Energy Rating
Profile of
Scheme 1 Scenario 3
(i.e. 75% of Original
R&D Lab Floor Area)
Buiding Energy Use
Intensity
4
Solar HleatGains
Figure 6.0.2. Overhead schematic of site massing with building identification letters.
Sensitivity of Load Diversity to Lab GFA
3.5
3.0
2.5
u. 2.0
---
Winter Heat
-U-Winter Electric
1.5
-*-Summer Heat
-0-summer
Electric
1.0
0.5
0.0
100%
25%
50%
75%
Percentage of Original Lab Space
%0%
Figure 6.1. Energy Sensitivity Analysis
of site design on operational energy, however the computational power required for these
are beyond the scope of this thesis. I perform a solar radiation analysis on the pedestrian
level of each scheme as a proxy for daylight and views access.
II.II.II Results
Energy Performance I For Scheme 1, the overall Load Diversity factor decreases
as you reduce the percentage share of Lab GFA. This indicates that the less lab space you
have, the more suitable the site is to cogeneration. See Figure 6.1. Conversely, the diversity specific to summer heating loads shows an upward trend after the 50% Lab space
scenario. This trend can be attributed to a few factors. The summer heating loads consist
of domestic hot water and cooling loads 2 . If daytime-load dominant uses, like the aca-
fect, radiative transfer between buildings, or urban wind velocities, other tools exist to provide a comprehensive picture of end use energy consumption at the neighborhood scale.
The cooling capacity on trigeneration systems can be achieved in one of two ways: Use mechani2
cal power to drive a vapor compression chiller or use waste heat from a gas or steam turbine to drive an
absorption chiller ( Harvey 2006).
demic use, increase over a certain threshold, their heat utilization may increase the
Net Present Value (NPV)
load diversity.
$404
$450
fttLf $355
-$350
Financial Performance I The data
S$250
$162
indicate that the reduction of Lab floor area
S$100
$76
50
is negatively correlated with the profit-
$0
1oo%
ability of the development. In other words,
the less Lab space, the less profitable the
development. (See Figure 6.2). In the 75%
50%
7S%
25%
0%
Percentage of Original Lab Space
Figure 6.2. Sensitivity analysis of the total site
Net Present Value.
Lab scenario, the DE would have to replace
revenues totaling 49 million dollars (100%
Net Present Value of Energy Savings
$300,000
NPV-75% NPV). This trend in profit loss can
be attributed to three major factors. First,
at 65$ per square foot, the rents are the
highest of all the leasable space. Second,
the buildings are
costly.3
$260,456
$213,301
$250,000
$200,000
4 $150,000
$136,831-.
$100,000
$61
$50,000
$0
100%
50%
75%
25%
Percentage
of Original LabSpace
When buildings
are erected in the first phase, however, 5
years of cash flow is collected from this
0%
Figure 6.2.1. Sensitivity analysis of the net present value of energy savings.
space. Third, the market research conducted by students indicates that this area
Sensitivity of Radiation
(kWh/m2)
can absorb Lab space, thereby making it a
lower-risk investment and a highly desirable use for the site.
--
Radiation (kWh/m2)
786
7,4
794
803
804
100%
75%
50%
25%
0%
Beyond NPV, the energy cost savings increase as the percentage Lab space
decreases. This savings trend, when dis-
Because of their specialized ventilation
3
and circulation systems, Lab buildings are typically
more expensive per square foot that non-specialized commercial buildings, such as conventional
office use.
Figure 6.3. Sensitivity analysis of ground level
solar radiation on site as proxy for pedestrian
counted over a 15 year period accounts for .06% of the baseline project NPV (savings of
$260,000 divided by $404 million baseline NPV). The energy cost savings do not provide
incentive to reduce lab area. However, the model does not account for: capital costs, revenues from liberated floor area in mechanical rooms, or other fringe benefits of DERs.
Physical Performance I The data indicates that each iteration increased solar access at ground level (tested at 1.7 m above ground surface). Given this, the changes in solar access were not significant among the sensitivity analysis (see Figure 6.3). The baseline solar exposure is 1400 kWh/m2 - the mean annual solar exposure of an openspace
exposed completely to day lighting. The change in solar exposure was less than 2% from
the 100% to the 0% scenario. (See Figure 6.4).
To provide more solar access and clear views to open space, the reorganization of
the masses adhered to the following trend: Base buildings (Lab and Academic) became
shorter as towers (residential) became taller. Despite the height increases on the G building group, their affects of remassing were minimized - the D2 and E3 base buildings decreased in height as that volume was shifted to the B2 base building. Academic space was
redistributed into the Lab space on Main Street, so the A,B, and C base buildings maintained similar heights throughout the experiment. Increases in the base building I (Conference Center) floor area had no significant impact because the overall area amounted to an
extra floor over the entire sensitivity analysis.
II.llI.IIl Conclusion
The diversity factor for summer heating loads is nearly the same between the 75%
and the 0% schemes. The NPVs, however, vary dramatically between the two. The 75%
scenario is 473% more profitablethan the 0% scenario. Figure 6.5 represents a greater
benefitsgap for the 0% scenario, although the load diversity is the same at the 75% scenario. In other words, the 0% scheme will cost more to achieve the same load diversity as
the 75% scheme. From the perspective of a developer or planner, this conclusion is an
ideal argument for maintaining the best use of the site while optimizing for energy planning. However, the solar radiation results do not significantly support such a conclusion.
761
w
0
0
~ *~3
Figure 6.4. Solar radiation sensitivity analysis through massing studies.
Adding four residential towers along Main Street would have significant impact
on the energy performance of the overall site. Each tower must be connected on ground
level to a lobby and then serviced by an elevator; elevators consume 5-8% of energy in
buildings. This may explain the flattening of the load diversity curve along as more energy
is consumed by elevators in the overall site design. This elevator consideration, also supports the argument for selecting the 75% scenario over the others. The additional cost of
elevators may also exacerbate Benefits Gap B. (See Figure 6.5). Benefits Gap B describes
a $375 million difference in value from the 0% Lab to the 100% Lab scenario - meaning
the DER should generate equal revenues in benefits above the baseline scenario,
Acomprehensive analysis of the total energy impacts of site design and use-mix
may influence this conclusion. Further, comprehensive cost and benefits analyses will
complete the value of energy savings and explain the meaning of the benefits gap.
'Benefits Gap' Disparity between 2 Scenarios of the Same Load Diversity
3.5 -
3.0
Benefits Gap A
-
Benefits Gap B
$450
$400
2.5 .
$350
. 2.0
Same Load Diversity Factor
$300
=0
$200
0
01.5 -$250
1.0 ~
$150
$100
0.5 $50
$0
0.0
100%
75%
50%
25%,
0%
Percentage of Original Lab Space
-r-Summer
Heat -NPv
Figure 6.5. Exploration of multivariable benefits analysis for sensitivity of use-mix to lab space reduction.
References:
Chen et at. "Study on sustainable redevelopment of a densely built up area in Tokyo by introducing a distributed local energy supply system." Energy and Buildings. 40 (2008):782-792
Chow et aL. "Building-mix optimization in district-cooling system implementation." Applied
Energy. 77:1 (2004): 1-13
Dhakal and Hanaki. Improvement of urban thermal environment by managing heat discharge
sources and surface modification in Tokyo. Energy and Buildings, 34:1 (2002): 13-23.
Harvey, Low Energy Buildings and District Energy Systems. (London: Earthscan, 2006), 572.
Heiple and Sailor. Using building energy simulation and geospatial modeling techniques to
determine high resolution building sector energy consumption profiles. Energy and Buildings.
40(2008)1426-1436.
Oak Ridge National Laboratory, 2006. ORNL CHP Capacity Optimizer. Accessed 11/2011. http://
appsl.eere.energy.gov/buildings/tools-directory/software.cfm/ID=495/pagename=alpha-list
Parshall et al. "Spatio-temporal patterns of energy demand in New York City and implications
for cogeneration." Working paper. 2010.
Veolia Energy. "Green Steam- An Urban Solution." http://files.eesi.org/dicroce_092311 .pdf
Yamaguchi et aL. "Development of district energy system simulation model based on detailed
energy demand model." Eighth International IBPSA Conference.7/11-14/2003.
Yamaguchi et aL. "Proposal of a modeling approach considering urban form for evaluation of city
level energy management." Energy and Buildings, 39:5 (2007): 580-592.
801
Part IV
821
CHAPTER VI
Urban and Architecture Design Proposal
Part III explains the final design proposal that resolves the issues of meeting real
estate demands and power demands in Kendall Square. This exercise allows the thesis to
focus on the building massing, overall siteplan, and CHP plant design without detailing every building. Section Idescribes the site approach and design goals that resulted from the
previous literature reviews, planning principles, and use-mix studies. Section Il describes
the final site program and design, starting with key focus of the public space and CHP
plant, then circulation and block structure, then the different site areas and spaces, then
to details of building massing. Part III describes how the design decisions meets each of
the issues defined in the prior text, includes load diversity, location of physical plant, the
combination of occupant and energy circulation, block structure, and phasing.
111.1 Site Approach and Goals
Winston Churchill once said, "We shape our buildings, thereafter they shape us."
The design vision for this site incorporates energy with culture, linking production, consumption, program and user behavior. The scheme uses the CHP plat as a new icon for the
MIT campus, distributes energy dashboards as public space anchors and links building
circulation with energy infrastructure.
CHP plants are historically hidden for auditory, visual and cultural reasons. Figure x describes the massing relationships of CHP plant to building. The proposed design
breaks these norms with the centerpiece of the site-plan, a dual facility that makes adjacent energy production and public space. Figure 7.1 describes how anchoring public space
with energy systems can effect urban form.
The architectural configuration of these two spaces elegantly blends the building
skin of the CHP plant with an outdoor amphitheater. Underneath the seating is a proposed
extension of the MIT Museum, a space married with the CH P plant. The architecture brings
users closer to the source of their energy,
thus impacting the perception of energy
behavior for the entire east campus. Figure
7.2 describes the spatial operations that
yield the architectural form.
This thesis uses existing institution-
programs from MIT to influence public
.al
space design. To create change in the way
occupants use energy in building, MIT has
instituted the Efficiency Forward Program,
with a grant from NSTAR, to reduce energy
consumption through behavior change. The
program has manifested as a competition
among dormitories that uses 'energy dashboards' to monitor energy use.' In 2009,
prize money of $10,000 was granted to the
dorms with the greatest reduction in energy use, based on a per building baseline2 .
Similarly, the Duke Energy model in Char-
\V
Lotte, NC, utilizes lobby displays in Commercial buildings energy usage- compar-
ing usage between buildings and targeting
systems for improvement. The proposed
Ll
scheme anchors the minor public spaces
with urban scale energy dashboards, pro-
841
Figure 7.1. Showing the potential relationship
between onsite energy production and urban
Energy dashboards, typically digital
1
screens, display the energy use buildings and intend to influence occupant behavior.
2
"MIT Dorms vie for greatest energy reductions." MIT Energy Initiative website. Accessed
form.
12/12/2011. h_
webmtedumte___m_
s
viding pavilions where energy education
and awareness can take place. Figure 7.3
describes the placement of these pavilions
in relationship to the central plant and exMaking Plant Visible
isting context.
The distribution systems of DERs
(hot water piping, electric conduit, chilled
water piping) operate under prohibitive regulation. The site design looks at this barrier
Using Icon Of Dome
as an opportunity. By bridging public right
of ways with distribution infrastructure,
the building masses connect on the upper
levels. In addition to moving energy, these
connections can move people. By linking
Joining With Public Space
private and institutional buildings through
an 'Energy Skywalk' , academic and private
researchers occupy one campus. This de-
CULTURAL PROGRAM
sign feature emulates contemporary office
design (like the Google Campus) to create
'zones of serendipity' where innovation is
proven to occur. Figure 7.3.1 describes the
'Energy Skywalk' as it passes through each
building mass, connecting to the central
ENERGY
plant.
EDUCATION
111.11 Site Program and Design
The site plan is made of paths and
places. Site circulation embodies major
goals of view and movement for pedestrians, bikes, and automobiles. Two major
Figure 7.2. Formal and programmatic manipulations to arrive at
architectural form.
Figure 7.3. Central Plant and Energy Dashboards.
I
Figure 7.3.1 Energy Skywalk.
~
-
(ji;
Figure 7.4. Existing Site
Figure 7.4.1. Circulation Planning.
Figure 7.4.2. Parcel planning.
Figure 7.4.3. Use planning.
paths are defined at the beginning of the scheme, one connects east to west campus, the
second connects Kendall Square south to the Waterfront. Providing these axes improve
the existing conditions of the site, increase the user convenience, and provide a more cohesive identity to the campus. Figure 7.4.1 describes the circulation paths that provide
North-South and East-West access.
The paths serve as boundaries for the new block structure of the site. At this stage
of planning, these areas can be perceived as the new parcels of the site, where one or
more buildings can occupy. See Figure 7.4.2. As previously mentioned, the site is divided
into zones of best use, with laboratory and retail along Main Street, Residential and Hotel
near the waterfront, and Academic use in between. This creates a mixed-use site, where
different uses work symbiotically to create a dynamic ground level user experience. With
the addition of residential towers above academic spaces and laboratory above retail, the
site becomes vertical mixed-use. This enhances the site by providing twenty-four hour use
in all zones of the development.' Figure 7.4.3 describes the horizontal and vertical mixing
of uses. Figure 7.5 is asection drawing that shows the mixing of uses both horizontally and
vertically.
The site program calls for a high density development. Providing adequate views
and solar access are a function of the building massing. The site deploys a podium and
tower strategy, popular in many high density cities. Programs that require no light (i.e.
laboratory clean rooms, academic auditoria, machine shops, mechanical rooms) are embedded within the core of these podiums, while functions that require solar access (i.e.
classrooms, office space) occupy the periphery of the podium. See Figure 7.6 which describes the overhead use-plan of the site.
The primary building masses are placed atop the podia. The width of each building
mass is standard to its use. Laboratory masses are 120' wide, office 90' wide, and residential 60' wide. These approximate footprints were provided in the RED Studio exercise
and were adopted for this massing study. The masses are vertically adjusted to maximize
'Twenty four hour use' describes the use of the public realm during the night by residents and
3
daytime use by the student and professional users of the site.
881
Figure 7.5 Transverse section through site. Note the mixing of uses both horizontally and vertically.
189
daylight exposure along the Main Street Plaza and in the central open space on site. See
Figure 7.7. Finally the residential towers are placed atop the base buildings to allow for
maximum views and solar access.
The Main Street Laboratory and Academic buildings take on a sawtooth floorplan
to break the monotony of large glass fagade treatments, which are native species in Kendall Square. The residential towers are circular in plan to provide optimal views and solar
exposure for residents. Each tower has a different profile as a commentary on the complexity of the design. The market rate residential towers to the west may be more profitable than the hotel towers to the east. Therefore, the bevel of the tower decreases from
east to west, leaving the hotel practically cylindrical. Each of the building masses are
linked by the 'Energy Skywalk' at the podium level where rooftop public spaces are common between public and institutional users. Car parks are located below each of the base
buildings and accessed by Main Street and Amherst Street. See Figure 7.6.3.
90|
L-
M
ENERGY FACILITY
MIT MUSEUM
TRANSPORATION
RETAIL
LABORATORY (COMMERCIAL)
OFFICE (ACADEMIC)
CONVENTION
HOUSING -MARKET RATE
HOUSING- GRADUATE DORM
lb
Figure 7.6. Land Use Plan
PEDESTRIAN PATHS
GROUND PATHS
JELEVATED
Figure 7.6.1. Circulation Plan
OPEN SPACE
GREEN SPACE
Figure 7.6.2. Greenspace Plan
Figure 7.6.3. Parking Plan
PARKING
LRLiLi~
4
RESIDEN IAL TOWERS
ACADEMIC AND LAB
GROUND PLANE
Figure 7.7. Exploded siteplan.
Note the massing adjustments
for solar access on ground level
(yellow).
921
Ir
U-
T
Figure 7.9. (Above) Rendering of the main public
space. Note the CHP plant.
Figure 7.11.2. Model of mixed use podium and tower.
1 Residential Entrance
2 Academic Space
3 Mit Museum
4 Power Plant
5 Amphitheater
941
TT7TJ I j
V-
err
Kim
V~L
,-~--z--~-~
-
__
Figure 7.11. Plan of CHP Plant and MIT Museum
1 Cogeneration Facility
2
Museum
Floor
3 Amphitheater
4 Stair To Second Level Plaza
5 Exterior Walkway / Energy Conduit
961
.....
MIj$
00l
981
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Page 99-100
Conclusions and Next Steps
Energy Planning and Design inan Urbanizing World
Goals in Energy Planning
In this thesis I describe a method to integrate distributed energy resources at the neighborhood scale during the design and planning stages of adevelopment. This method shows
the potential to right-fit development schemes to the energy demands of DERs through
use-mix sensitivity analysis. This methodology can inform both stakeholders of domestic mixed-use development trends and rapid-urbanization in developing countries alike.
Where many studies focus on minimizing energy demand, this study focuses on refining
the nature of that demand, namely through optimizing load diversity.
The energy planning exercise shows that the real estate and energy demands of a
development can be elegantly reconciled with a holistic approach. I conducted a load balancing analysis that is transferable to small and large scale developments alike. The design proposal, also, provides transferable lessons of high density development and siting
power plants within mixed-use, urban districts. These lessons can inform policy decisions
from building code to the scale of urban zoning code.
Energy planning raises new concerns within the existing paradigm of real estate
development, thus contributing both philosophically and financially to the concept of
highest and best use. Though energy systems are financially represented in the existing
paradigm of valuation (NPV), DERs capture key hurdles of larger power networks at a controllable scale. Most on-site energy systems (e.g. wind, solar photovoltaic (PV), solar thermal) operate in the existing paradigm of CHP, that systems are sized for the development.
This thesis reframes the value-drivers of a neighborhood scale development by increasing the weight of energy system demands when considering use-mix valuation. As long as
maximum profitability defines a project's success, the value-drivers should reframe the
calculation of the project's Net Present Value. All energy initiatives, ranging from efficien1101
cy upgrades to renewables installation, can use a similar question to that of this thesis,
allowing key development factors like use-mix to acquiesce to a larger goal of sustainable
development.
This study furthers municipal government efforts of emissions reductions through
its process of planning, evaluation and redevelopment of neighborhood scale sites. DERs
provide versatile options for energy suppliers to meet growing demand. Additionally, DERs
future proof assets - that is, protect against the future rise of fuel prices. In this way, DERs
can reduce risk on the side of the lender, thus making it easier and cheaper for the development to obtain funding. Further, DERs' versatile fuel source options provide end-users
with added security against sharp fuel price changes, creating an energy future proofing
of fuel source flexibility.
I purposefully omit the overall energy efficiency and overall fuel demand of the
development scenarios. The schemes were not compared on the merit of total energy consumption because this thesis focuses on fuel source efficiency and the benefits of a specific energy system. The research recognizes that reducing overall energy demand is a key
component of sustainable development and contributor to emissions reduction. I chose
the topic of DER in part, because energy efficiency is well represented in real estate, policy
and design literature.
Next Steps: Policy Implications
Chapter IV addresses programs that have redefined the value of energy systems
and incentivized alternative energy system futures. I conclude by proposing heat districts
of variable sizes using overlay zoning, or what I call Energy Overlay districts. How would
one go about this? What are the alternatives to regulating through use-mix and how do
they incentivize or dissuade development and design communities?
In Chapter IV,the policy proposal mandates energy districts, which implies some
responsibility for the energy systems on part of the public entity. A city or state policy
could be implemented like the Danish Heat Planning Act. First, is the heat planning exercise descriptive or projective? Do you identify existing critical mass or id desired poten-
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tial area that benefit from the economic boost of mixed use? Second, who pays and how
quickly are these districts established?
U.S. ownership structures for DERs vary from municipal to NPO to private. If the
energy districts were voluntary, great public subsidies would be required for Cambridge
to invest in distribution, generation, and building system retrofit before private sector
found the investment profitable. If Cambridge mandates strict redevelopment of energy
districts, the city would create immediate demand with financial burdens falling on building owners and taxpayers.
An alternative to municipal driven planning studies are ad hoc studies conducted
during the site approval process. Development approval protocol exist, in part, to explore
municipal interests. Cambridge can incorporate intensive energy study requirements in
approval protocol like environmental impact assessments (EIA), environmental impact
reports (EIR). These studies historically come at the developer's expense. ElAs and EIRs
check proposal impacts against national, state and local standards, such as the Environmental Protection Agency (EPA) standards for Brownfield reclamation.
Requiring a use-mix sensitivity analysis for DER feasibility allows developers to
see benefits themselves without the need for mandating. As a policy lever, city officials
would require the sensitivity analysis through the approvals process at first schematic development phase, land purchase and ownership change agreements. An expert team may
be necessary from the city to review the submission. The danger in this option is potential
conflicts with other site approval protocol - for instance, the energy study may conclude
that housing is not ideal, though it is a site required to have an affordable housing component.
Next Steps: Modeling Energy Profiles
Building energy data is a cornerstone of use-mix studies like the one presented
here. Data validity is key to site scale energy modeling to effectively quantify the benefits
of these systems. When reviewing similar studies, one should ask: "Where is the projected
energy use data coming from? How are emissions being calculated? Is it representative of
contemporary and future urban conditions?" Among these conditions are future climate
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forecasts, site design to energy demand relationships, and external sources of load balancing.
Researchers aggregate data from multiple sources to generate urban scale load
profiles or use simulation software to generate demand data. Energy models like the Urban Modeling Index (UMI) are increasingly inclusive of energy interactions among groups
of buildings. These tools are entering into the design process at early phases intended
to minimize annual energy consumption through site design, Design phase studies can
utilize these tools to test use-mix configurations that automatically produce numbers on
emissions, primary fuel use and temporal energy demand.
The behavior of energy models will be affected by climate change. Energy demand
will react differently to climate change scenarios depending on the specific building form,
envelope and siting. These factors determine how exaggerated weather conditions will
influence building energy use. Such as those projected to occur in the year 2030, a study
conducted in Massachusetts found that 2030 climate scenarios led to a reduction in electric and heating fuel oil use in the winter and an increase in electric demand in the summer (Amato et al. 2005). The study predicted significant demand growth, meaning use-mix
studies conducted over time will have long term demand when uses change. The 2030
scenario projects demand rising above 130% of the baseline, which is the climate average
from 1960-2000. The study also suggests a need to incorporate the impacts of climate
change on regional energy system planning, a prospect for DERs to either satisfy the additional demand by climate change or satisfy demand from new development. The takeaway
for users of district systems is to incorporate climate change scenarios when designing
the system capacities, and understand how the development as a whole responds to those
scenarios.
Chapter VI outlines some relationships between site planning attributes and the
operational energy use of buildings. The experiment performed on the Kendall Square
site used a massing study to model operational energy use throughout use-mix sensitivity analysis. I postulate the energy performance of each scenario will demonstrate greater variance with greater constraints to development. If the site were more constrained
1041
by height, the solar implications would be exacerbated through the sensitivity analysis.
With the current scheme, podiums-base buildings and towers, the actual footprints of the
buildings do not affect the openspace, and thus access to daylight. Redesigningthe existing use-mix with lower buildings and the same floor area means less ground space, which
could translate to lower solar access. In other words, to see greater solar variation, the
massing studies need greater variation, exploring multiple massing study variations.
Aside from building operational energy, site-planning can enable additional benefits that affect energy demand. In Chapter III, the concept of load balancing is shown to
be key for successful DERs scenarios. Load balancing can be achieved by means beyond
use-mix variation. Electric vehicles, smart appliances, and renewable energy technologies can balance energy demand at a site scale. Site-planning influences the capacity of
these technologies. For instance, the allocation of electric vehicle parking spots and docking stations impacts the balancing capacity of the electric vehicle stock. In compact development sites, this space is valuable and thus competes with leasable floor area. The
site-planning exercise resolves these cost-benefit relationships and thus has a complex
impact on energy demand.
Next Steps-Cost-benefits -
New items for consideration
In Chapter II, this thesis outlines costs and benefits of DERs from the perspective of a developer in an attempt to define the components of NPV that pertain to energy
systems. However, the financial component of the sensitivity analysis fails to incorporate these finding. Costs, savings, and revenues from DERs require further research to enhance the relevance of studies such as the use-mix sensitivity analysis conducted in this
thesis. Studies should go beyond traditional feasibility analyses that compare in-building
heating and cooling systems with DERs. This research has identified two sources of savings germane to DERs; namely, reduced interest rates in lending and monetized emissions
savings.
Risk assessment for lending practices includes myriad factors, from the reliability
of the developer to the market analysis to the cost of goods. However, seldom are alternative energy supply options identified as a source of reducing risk profiles. Rising fuel costs
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and rising demand per square foot from climate change translate to higher total overhead
per tenant. Even with triple net leases (where owners pass utility costs to tenants) total
overhead cost is higher when the per unit energy cost is higher. By introducing DERs, benefits like fuel flexibility and price risk hedging on fuel can reduce the per-unit energy cost
compared to traditional grid energy. Additionally, the power quality security provided by
DERs are pertinent to the operation of businesses such as medical facilities and data centers, reducing the risk of losses in business operations. Making this connection with the
lending community could result in lower interest financing for buildings and infrastructure
connected through DERs. This, in turn, affects the system cost as a higher interest financing becomes more costly over time.
In addition to financing benefits, secondary revenue benefits may be achieved
through the adoption of DERs because they reduce the carbon footprint of building operations. As mentioned in Chapter 1I1,carbon markets exist at the building scale, e.g., the
Tokyo Cap and Trade system implemented for commercial structures. In a world where
districts or single buildings enter into carbon 'cap and trade' system, developments supplied by DER trade their emissions credits, potentially for additional revenue. This scenario
implies that revenues stay among the participants and are not absorbed to by the municipality or state. The significance of this cashflow depends on the value of the emissions
credit on a dollar per ton basis.
Concluding Thoughts
This thesis reframes the priorities of real estate development to prioritize lower
emissions site-scale scenarios. The methodology in Chapter VI can be used to guide lowercarbon development decisions from public, private, and civil parties. Energy planning at
this scale creates a manageable scenario to capture the holistic profile of energy inputs
and outputs to a section of the city. Energy planning studies at this scale can seed larger
models that attempt to account for granular energy behavior.
Neighborhood scale energy planning faces challenges of user perception, site design, financial support and immediate environmental concerns. Future work should consider the many representations of DER, such as its agility in scale, function and physical
1061
manifestations. Domestic adoption of DERs requires private sector development to engage; they are slow, however, to adopt alternative practices. Ultimately, DERs provide a
value proposition that is complex and require clarity to generate consensus of their merits.
107
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List of Figures
Figure 1. Illustration of Centralized versus Local Energy Production.
Figure 1.1. Example comparting cogeneration and centralized power production.
Source: Andrews 2008.
Table 2. Use-Mix of Schemes 1-4.
Figure 2.1. Aerial Image of Greater Boston Area. Site outlined in red.
Figure 2.2. Siteplan with existing buildings. Dotted lines indicate program zones of
highest and best use.
Figure 2.3.1-4. Site proposals for Kendall Square Site.
Figure 3.1. Demonstrates high (below) and low (above) load diversity.
Figure 3.2 Demonstrates high (below) and low (above) service factor scenarios.
Figure 3.3. Illustration of development phasing plans. Above, the plans have a centralized plant. Below, the plans have distributed plants for each parcel or building.
Figure 3.4. The energy diagrams (right) show possible energy supply plans over
time.
Figure 4: Illustration of Danish Heat Planning districts. Source: IEA 2008.
Figure 4.1. Illustration of existing district steam systems in the City of Cambridge.
Figure 4.2. Cambridge's K2C2 re-zoning plan and improvement district.
Figure 4.3. Potential sizes for energy overlay districts.
Figure 5. Building Energy Demand Profiles from Simulation measured by Area.
Notice the Startup loads at 5:00 am for Office and Lab Uses and dropoff of Residential between 9:30 and 10:00am.
Figure 5.1. Energy use of each building type is stacked to show an overall demand
profile of the simulation day.
Table 5. Comparison of schemes by floor area distribution.
Figure 5.2. Comparison of schemes by floor area distribution.
Figure 6. Process of sensitivity analysis.
Table 6. Floor area breakdowns.
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Figure 6.0.1. Schematic of methodology and tools.
Figure 6.1. Load Diversity Analysis.
Figure 6.2. Sensitivity analysis of the total site Net Present Value.
Figure 6.2.1. Sensitivity analysis of the net present value of energy savings.
Figure 6.3. Sensitivity analysis of ground level solar radiation on site as
proxy for pedestrian comfort.
Figure 6.4. Solar radiation sensitivity analysis through massing studies.
Figure 7.1. Showing the potential relationship between onsite energy production and urban form.
Figure 7.2. Formal and programmatic manipulations to arrive at architectural form.
Figure 7.3. Central Plant and Energy Dashboards.
Figure 7.3.1 Energy Skywalk.
Figure 7.4. Existing Site.
Figure 7.4.1. Circulation Planning.
Figure 7.4.2. Parcel planning.
Figure 7.4.3. Use planning.
Figure 7.5 Transverse section through site. Note the mixing of uses both
horizontally and vertically.
Figure 7.6. Land Use Plan.
Figure 7.6.1. Circulation Plan.
Figure 7.6.2. Greenspace Plan.
Figure 7.6.3. Parking Plan.
Figure 7.7. Exploded siteplan. Note the massing adjustments for solar access on ground level (yellow).
Figure 7.8. Ground floor siteplan.
Figure 7.9. Rendering of the main public space. Note the CHP plant.
Figure 7.10. Siteplan.
Figure 7.11. Plan of CHP Plant and MIT Museum
Figure 7.11.1. View of amphitheater from elevated plaza. View of MIT Museum interior.
1101
Figure 7.11.2. Model of mixed use podium and tower.
1111
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